Nature Physics

Surface curvature is a fundamental geometric cue in tissue morphogenesis, yet its role in guiding collective cell organization has remained elusive. Here, we show that curvature acts as a geometric control parameter that shapes supracellular alignment and chirality while modulating myogenic differentiation in myoblast tissues. Cells cultured on curved substrates self-organize into robust helical assemblies whose handedness is set, and can be reversed, by the sign of curvature: convex fibers produce right-handed helices, whereas concave channels invert the chirality. We identify a previously hidden clockwise bias in single-cell motion associated with the helical actin cytoskeleton. A minimal continuum theory coupling an effective chiral drive to curvature quantitatively captures the emergence and reversal of tissue-scale chiral alignment. On substrates with spatially varying curvature, local curvature gradients organize patterned multicellular architectures while preserving a global handedness. Curvature is also associated with myogenic state, with higher curvature linked to reduced or delayed differentiation. Together, these findings reveal how complex geometries shape the alignment, symmetry, and cellular state of living tissues.

Cellular activity drives epithelial fluidization -- a widespread phenomenon observed during tissue development, remodeling, and repair both in vivo and in vitro. Yet the physical origins and spatial organization of active forces vary widely across biological systems and are often represented by a single generic mechanism in theoretical models. Here, using an active vertex model, we systematically compare four modes of epithelial activity spanning subcellular to tissue scales: apolar motility, polar motility, fluctuating contractility, and mechanochemical regulation. Although all four mechanisms drive the same global transition from a solid-like rectangular tissue to a fluid-like circular morphology, they reach this state through distinct pathways -- differing in the rates and topology of junctional rearrangements, cell elimination, and collective motion and leave distinguishable signatures in tissue architecture, cell dynamics, and mechanical relaxation. Among these observables, spatial velocity correlations directly capture the spatial organization of activity: their correlation length and functional form together resolve all four mechanisms. The robustness of these signatures across activity strengths suggests that spatial velocity correlations offer an experimentally accessible means of identifying the physical origin of epithelial activity from live-cell imaging alone.

Although topological defects in cell monolayers have been recognized as mechanical organizing centers in morphogenetic processes, the mechanism by which cells coordinate their motion at such defects and self-organize into higher-order structures remains elusive. Here, we report the formation of three-dimensional (3D) multicellular mounds in unconfined myoblast monolayers, at well-controlled vortex topological defects. Prior to the onset of bilayering, the vortex structure induces millimeter-scale cell flows converging toward the defect center. As a result, 3D cell mounds form at the defect core, layer-by-layer. These mounds grow by interlayer permeation sustained by the converging cell flows. At late stages, the bell shape of the structured mounds can be modeled with a dynamics driven by these converging flows. Our results therefore highlight the crucial role of integer topological defects in driving large-scale cell flows yielding the formation of highly ordered 3D tissues from a monolayer. We propose that similar mechanisms may be at play in certain morphogenetic and tumorigenic events.

Enzymatic reactions in biomolecular condensates are often assumed to be regulated through local enrichment of reactants. However, condensates also reshape molecular transport and reaction kinetics, making it unclear how phase separation controls catalysis in living cells. Here, we develop a quantitative theory of biomolecular catalysis in phase-separated systems and find that liquid condensates can act as tunable catalytic switches, transitioning between regimes of enhanced and suppressed enzymatic activity, exhibiting optimal responses at biologically relevant condensate sizes. We show that condensate-mediated catalysis cannot be understood from reactant enrichment alone, but instead emerges from the coupled interplay of molecular partitioning, diffusive transport, and phase-dependent reaction kinetics. The strongest regulatory effects occur under rapid interphase exchange, where the spatially heterogeneous catalytic network admits a system-level Michaelis-Menten description governed by system-averaged concentrations and reaction kinetics. Our framework predicts that micron-sized condensates can either enhance or suppress enzymatic activity by up to two orders of magnitude, and that optimal catalytic regulation can emerge at condensate sizes comparable to many biomolecular condensates. These results provide experimentally testable predictions for condensate-mediated catalysis and establish quantitative principles for understanding and engineering enzyme-catalysed reactions in biomolecular condensates.

Despite substantial variation in adult size, animals within a species maintain consistent tissue patterns and shapes, a core property known as developmental scaling or size invariance. Developmental scaling has predominantly been attributed to the scaling of morphogen gradients and gene patterns to maintain positional information and cell fate specification1,2. However, development also necessitates collective cell flows that reshape tissues and reposition cells3,4. How these flows adapt to body size remains unclear. By combining quantitative live imaging, experimental perturbations, and physical modeling in the Drosophila thorax epithelium, we address this question in the context of a fundamental process: collective cell migration. We find that migration velocity scales linearly with tissue size, accounting for size-invariant cell positioning. While gene patterning scales with tissue size and modulates force generation, it is not sufficient to ensure proper velocity scaling. Instead, tissue mechanical properties govern the dependence of migration velocity on tissue size, enabling developmental scaling within the physiological range of animal sizes. These findings uncover principles and limits of size invariance by revealing how tissue mechanics sets the scaling behavior of collective cell flows with organismal size.

Epithelial cell shape plays a fundamental role in tissue dynamics. Numerous studies have established how cells drastically change their shape to promote epithelial tissue morphogenesis. However, the mechanisms enabling cells to maintain their shape remain far less understood. Here, leveraging live imaging in Drosophila epithelial tissue and theoretical modeling, we identify an emergent mechano-chemical feedback that ensures junction length and cell shape stability, without requiring a dedicated molecular force sensor. We find that an increase in junction length is associated with a passive dilution of E-Cadherin, followed by an increase in Myosin-II-dependent contractility that reduces junction length. Theoretically, we show that this regulation of junction length generically emerges when negative and positive regulators of contractility have distinct kinetics. Experiments confirm that E-Cadherin acts as a negative regulator with slow turnover. Mechanistically, local dilution of E-Cadherin passively lifts an inhibition on lateral apicobasal polarity components, allowing the RhoGEF Cyst -- with its fast turnover -- to accumulate and increase contractility. Perturbing this feedback results in aberrant cell junction and shape regulation, thereby compromising the ability of the tissue to buffer local mechanical fluctuations and global mechanical stresses. Altogether, we propose that differential turnover between apical and lateral polarity complexes provides an emergent mechano-response for junction length and cell shape homeostasis.

Delamination within stratified epithelia like the skin epidermis describes the detachment and upward motion of cells originating from the basal layer. Despite its fundamental importance for tissue development, homeostatic regeneration and repair, the mechanisms that drive delamination remain a longstanding open question. Upward motion follows cell shape changes, which are inherently driven by physical forces, but their role is elusive. Here, we investigate delamination in stratifying keratinocytes by combining imaging, force measurements and theoretical modeling. We identify a local change in force balance between differentiating cells and their environment as the key step initiating delamination. Within a homogeneous cell layer with apically polarized contractility, differentiation leads to actomyosin remodeling, redistributing cellular force exertion to the basal side. Such mechanical heterogeneity then results in differentiating cells experiencing and inward basal and outward apical forces that manifest in the formation of a +1 force defect and promote shape changes culminating in upward motion. Simultaneously, delaminating cells actively pull on their underlying neighbors, generating convergent tissue flows which close the basal layer below. Together, we propose a general physical description of delamination initiation, which may act across various multilayered epithelia.

The collective spatial phenomenon of complement protein opsonization on nanoparticle surfaces is a key component of the immune response to viruses, engineered nanoparticles, and diseased cells. Recent work showed this opsonization follows a sharp, percolation-like transition versus the spacing d between surface-bound attachment sites, leaving two open questions: 1) whether the transition exhibits hallmarks of true criticality, such as diverging susceptibility, and 2) whether it can be distinguished from an alternative first-order cooperative (Hill-type) process producing an equally sharp threshold without true criticality. Here, we resolve both questions using a hierarchical statistical-mechanics treatment spanning stochastic, mean-field, and spatial reaction-diffusion models. The variance of two order parameters, peak complement activity and activation lifetime, diverges near threshold and sharpens systematically with system size, the defining signature of a critical point rather than a smooth cooperative response. Extending the analysis across site spacing and intrinsic kinetic rate constants traces a two-dimensional locus of critical points with consistent critical exponents throughout, establishing a single, robust universality class. The mean-field dynamic exponent for activation lifetime agrees quantitatively with the exact value predicted for the general epidemic process. Finally, a reaction-diffusion model of the nanoparticle surface shows the critical locus is set by a diffusion-limited length scale, establishing complement percolation as a fundamentally transport-limited surface reaction. These results place complement activation within the percolation universality class and identify the physical parameters, diffusion, catalysis, and decay, that govern its critical threshold, with direct implications for rational design of complement-evading nanomaterials, immunology, and evolutionary biology.

Cell shape changes during migration, division, or differentiation require the dynamic regulation of actin network mechanics. Actin crosslinkers are central to this regulation, controlling network connectivity and the transmission of contractile forces. A large diversity of crosslinkers exists, differing in length, domain structure, and binding kinetics, yet why cells deploy specific crosslinkers in a physiological context remains unclear. To bridge this gap, we developed a light-controlled actin crosslinker toolbox spanning three physiologically relevant lengths: ~9 nm (fascin-like), ~16 nm (fimbrin-like), and ~56 nm (alpha-actinin-like). Using magnetic pincher experiments and in silico modelling, we show that short and mid-length crosslinkers dynamically tune cortical stiffness and thickness in a density- and myosin-dependent manner, with short crosslinkers also driving pronounced stress-stiffening as the cortex is deformed. Strikingly, minute-scale activation reveals a length-dependent switch in cell behaviour: short crosslinkers cause cortical delamination, while long ones instead drive cell polarization and symmetry breaking. This switch can be overridden by perturbing actin turnover, which unlocks polarization in mid-length crosslinkers that otherwise delaminate. Crosslinker-induced polarization is not merely a local cortical event: it directs subsequent cell spreading, coupling a nanometre-scale molecular choice to a cell-scale decision about movement. Together, these findings establish a versatile optogenetic platform for manipulating actin crosslinking, and show that the cortex can encode a behavioural switch directly in its material architecture.

Contact inhibition of proliferation (CIP) enables epithelial tissues to self-regulate growth and maintain tissue homeostasis. However, how cell-level mechanical contact, tissue-scale structural order, and proliferation kinetics interplay remains a fundamental open question in living matter physics. Here, we present a particle-based model of a confluent epithelial monolayer governed by overdamped dynamics, where individual cells interact via a two-dimensional hard core- soft shoulder potential. By comparing structural evolution during quasistatic densification with previously reported experimental division kinetics, we find that the dynamics of proliferation arrest mimics the onset of direct steric contacts between the hard cores of the shell. Identifying hard core contacts as the physical driver of CIP, we couple our mechanical model with a stochastic Monte Carlo division scheme in which the instantaneous division rate decreases to zero from an intrinsic value as the number of hard core contact increases to six from zero. We demonstrate that for high intrinsic division rates, the cellular densification outpaces mechanical relaxation. This kinetic mismatch drives premature hard-core contact formation, shifts the onset of jamming and contact inhibition to lower packing fractions, and induces increasingly disordered transient configurations before the tissue universally converges to a hexagonal close-packed limit. Our model's predicted division kinetics and structural order evolution are consistent with epithelial monolayer experiments, both reported and our own. This minimal physical framework links single-cell steric contact mechanics directly to tissue-scale growth regulation and structural evolution.

Adult tissues maintain precise architectures composed of multiple interspersed cell types, yet prevailing models of cell fate patterning rely on pairwise interactions between neighbouring cells that generate binary decisions. How local interactions encode higher-order, beyond pairwise, multicellular organization remains unclear. Here, using the Drosophila midgut as a model of adult tissue self-organization, we identify a higher-order neighbourhood-sensing mechanism that couples cell identity, mechanics and stem cell (SC) fate. We show that the receptors Cirl/Latrophilin and Toll-8 are expressed in complementary cellular compartments, restricting their engagement to heterotypic interfaces between progenitors and differentiated enterocytes (ECs). These interactions generate interface-specific myosin II-dependent tension that depends on EC neighbourhood composition and mechanically gates Delta-Notch signalling. Thus, although Delta-Notch acts through pairwise interactions, these fate decisions are modulated by a higher-order mechanical state integrating information from surrounding cell contacts. A mathematical model incorporating this coupling reproduces multicellular tissue architecture from first principles and predicts that loss of higher-order coupling destabilizes progenitor organization. This prediction is consistent with the excessive fate transitions, topological disorganization and regenerative defects observed after Cirl-Toll-8 disruption. These findings establish higher-order mechanical neighbourhood sensing as a general principle by which tissues integrate local cellular identities to maintain and restore complex architectures.

While geometric constraints shape tissue development, quantifying the resulting growth dynamics remains a central challenge in tissue engineering. Conventional methods often struggle to capture multi-scale kinetics without complex labeling or difficult single-cell tracking. Here, we analyze geometrically controlled growth of microtissues derived from human dermal fibroblasts using time-resolved, label-free brightfield microscopy, combined with optical flow and semi-automated deep learning mitosis detection. By extracting multi-scale flow fields and integrating them with tissue segmentation, we quantify directional tissue dynamics, separating flow into parallel and normal components relative to the local tissue contour. Applying this framework, we contrast the quiescent tissue interior with the advancing growth front where localized dynamics and cell proliferation drive expansion. Our results demonstrate that, compared to the bulk, the growth front exhibits higher fluctuations parallel to the tissue contour, positive mean normal flow, and significantly increased mitotic activity. Furthermore, evaluating flow divergence around mitotic events reveals distinct spatial behaviors: with the onset of mitosis, a contraction and subsequent expansion occurs in the vicinity of the dividing cells. Beyond the immediate cellular neighborhood, the broader regional dynamics remain consistent before and after mitosis onset, with net tissue expansion in proximity to the growth front and contraction within the tissue interior. By extracting continuous kinetic data from easily accessible, label-free brightfield imaging, this approach serves as a non-invasive, complementary tool for evaluating in vitro tissue morphogenesis and growth dynamics. This analytical framework can be expanded to study locally resolved tissue morphogenesis and growth kinetics in other microsystems, ranging from embryos to organoids. Statement of SignificanceUnderstanding how localized cellular forces drive tissue growth is critical for mechanobiology. However, mapping these dynamics traditionally requires complex, invasive fluorescent labeling. We present an accessible, label-free computational framework combining optical flow and deep learning-based mitosis detection to quantify continuous tissue kinematics directly from standard brightfield microscopy. Applying this to 3D microtissues, we reveal a distinct spatial coupling between cell division, local mechanical fluctuations, and directed tissue expansion at the active growth front. This non-invasive approach bridges the gap between single-cell mechanics and macroscopic morphogenesis, offering a versatile tool to monitor complex in vitro model systems-like organoids and bioengineered tissues-without disrupting their native state.

Biological aging is accompanied by systematic changes in epigenetic modifications and chromatin organization. The reversal of the effects of aging, rejuvenation, is experimentally achieved by the transient induction of factors that modify these marks in cells and organisms. Here, we show that key features of rejuvenation experiments emerge from the biophysical interplay between dynamic epigenetic marks and the three-dimensional conformation of chromatin. Using a minimal field theory and molecular dynamics simulations, we show that the system responds in three distinct temporal regimes. The intermediary regime fulfills necessary conditions for successful rejuvenation. In this regime, the system spends time near a separatrix, allowing for high epigenetic plasticity, while memory retained in the chromatin conformation enables restoration of the original epigenetic correlations. Analysis of sequencing data further supports the predicted coupling between chromatin compaction and epigenetic correlations. Our results provide a physical explanation for how rejuvenation may remodel age-associated epigenetic states without irreversibly erasing cellular identity. We identify a general mechanism by which memory stored in a slow structural variable permits reversible remodeling of a faster internal state.

Early animal embryos undergo rapid cleavages that partition cytoplasmic volumes orders of magnitude larger than those of somatic cells1. Each division must reposition nuclei and centrosomes and distribute organelles within minutes, over distances up to hundreds of micrometers2. Cleavage furrows are positioned by microtubule asters3,4, but the mechanical mechanism for long-range transport of cytoplasmic components before cytokinesis was unknown. Here, we show that cytoplasm behaves as a locally switchable active material. Fluidization at the midplane allows bulk actomyosin to convert a local mechanical asymmetry into directed global flows of all components as a composite material. Using an actin-intact cycling Xenopus egg extract together with Xenopus and medaka embryos, we find that F-actin mechanically couples microtubule asters, organelles, nuclei and centrosomes into a gel-like composite that propagates forces over hundreds of micrometers. After mitosis, Aurora B kinase patterns a locally fluidized midplane, from which myosin-II contractility drives coherent cytoplasmic flows. A fluid dynamics model accounts for the observed flow geometry and rates. Our results reveal how local control of the material state of cytoplasm converts mitotic symmetry breaking into long-range intracellular transport and identify bulk actomyosin as the active stress generator that partitions embryonic cytoplasm as a composite gel.

Single-particle tracking is widely used to probe nanoscale dynamics in biological systems, yet most approaches rely exclusively on translational motion, overlooking rotational dynamics that offer complementary information about the local physical environment. Here, we present a simultaneous rotational and translational single-particle tracking approach using a vortex-engineered point spread function in a single detection channel. We validate this approach with static and freely diffusing nanorods, demonstrating accurate orientation recovery and quantitative agreement with theoretical predictions of rotational diffusion. Using a biomimetic lipid bilayer system, we show that translational and rotational diffusion exhibit distinct sensitivities to environmental perturbations, confirming that these two modalities capture complementary local environment information. Applying this framework to living HeLa cells, we show that combined translational and rotational diffusion signatures define distinct biophysical fingerprints of cytoplasmic and endocytic compartments and reveal compartment-specific responses to metabolic perturbation. Finally, time-resolved analysis of individual endocytic compartments uncovers dynamic changes in the local physical environment that are inaccessible to conventional translational tracking. By coupling translational and rotational readouts, this framework opens a new dimension for probing the physical organization and dynamics of living systems at the nanoscale.

Epithelial tissues continuously remodel their curvature during morphogenesis, homeostasis, regeneration, and disease, yet experimental access to time-varying curvature remains limited. Here, we introduce CurvoChip, a pneumatically actuated microsystem that reversibly deforms confluent epithelial monolayers cultured on a 20-m elastic membrane into concave or convex geometries. The device operates either in a standard incubator or on a microscope stage and provides programmable control over pressure amplitude, direction, and cycling. Analytical scaling, finite-element simulations, and confocal profilometry establish predictable membrane deformation across the operating range, whereas cycling between -400 and +400 mbar for 120 cycles produces stable deflection without detectable drift or residual deformation. We further implement a three-dimensional surface-reconstruction and segmentation workflow to quantify cell and nuclear morphology on curved monolayers. Acute curvature induction produces a marked polarity-dependent response: convex deformation causes greater cell spreading and epithelial thinning than concave deformation, while nuclear projected area, thickness, and volume change in a direction- and position-dependent manner. These results show that epithelial architecture is sensitive not only to curvature magnitude but also to its orientation relative to the apico-basal axis. CurvoChip therefore provides an accessible platform for dissecting how epithelial tissues integrate dynamic geometric cues.

Radiation-induced DNA double-strand breaks (DSBs) drive cellular mortality, mutagenesis, and severe evolutionary bottlenecks. While classical phenomenological models, such as the Linear-Quadratic (LQ) framework, reliably predict macroscopic population survival, they obscure the intrinsic single-cell stochasticity that governs critical rare events like tumor recurrence or the emergence of radioresistant persisters. To bridge this divide, we develop a mathematically exact stochastic differential equation (SDE) framework that models continuous DSB induction and repair as a Feller square-root process. By deriving exact closed-form expressions for the foci moments, we establish a highly efficient Maximum Likelihood Estimation (MLE) pipeline that circumvents computationally exhaustive Monte Carlo simulations, allowing the direct extraction of deterministic repair velocities and intrinsic molecular noise from empirical single-cell $\gamma$-H2AX data. Integrating this kinetic model with a cumulative damage hazard via the Feynman-Kac formalism, our framework seamlessly recovers the classic macroscopic LQ survival topology from microscopic first principles. Furthermore, systematic sensitivity analysis uncovers a fundamental evolutionary duality: while initial physical damage operates additively, ultimate cellular fate is driven by a nonlinear survival response governed by the trade-off between the damage hazard rate and intrinsic molecular noise strength. Crucially, we demonstrate that this molecular noise inherently enhances population survival. Governed by Jensen's inequality, stochastic variance acts as a non-genetic bet-hedging mechanism that buffers the population by favoring cells with transiently low damage loads. Ultimately, this exact stochastic framework bridges microscopic biophysics and macroscopic demographics, offering deep mechanistic insights into the evolutionary roots of radioresistance.

Locust swarming, one of nature's most spectacular examples of a repeated emergent polyphenism, has long been suspected to rely on conserved "swarming genes" or shared genomic features. By applying a model-clade approach comparing six species that vary in their degrees of plasticity and collective behavior, we show that the evolution of swarming locusts is not driven by shared genomic features or a universal set of swarming genes. In contrast, we find that this phenomenon evolved through flexible regulatory architectures, in which the degree of behavioral plasticity directly correlates with the total scale of density-responsive gene expression. While different locust species recruit largely non-overlapping gene sets to achieve the same syndrome, these divergent molecular machineries converge on similar higher-level biological functions. Thus, multiple molecular pathways achieve locust swarming, challenging the preconceived notion about the genetic prerequisites to transition from solitary to collective states. Further, we establish that a complex syndrome such as locust swarming emerges through modular regulatory systems that can be amplified, modified, or attenuated across the tree of life.

Long-range correlated motions couple distant regions of a protein, providing a physical basis for allosteric communication, cooperative conformational change, and the balance between structural stability and sensitivity to perturbations. Yet membrane proteins operate within a strongly anisotropic lipid bilayer, and how this environment reshapes such system-spanning coordination remains unclear. Using an implicit-membrane anisotropic network model, we perform a proteome-wide analysis of more than 3,000 human transmembrane proteins. We find that long-range correlations remain scale free under membrane constraints but become strongly direction dependent. Across protein sizes and topologies, their correlation lengths continue to scale with the corresponding molecular dimensions, while increasing membrane anisotropy extends in-plane correlations and shortens those along the membrane normal. Because spontaneous correlations and perturbation responses arise from the same underlying mechanics, we further resolve residue-level responses into in-plane and normal components. The resulting directional mechanical susceptibility provides new predictions of mutation-sensitive sites in GPCRs beyond those captured by conventional scalar flexibility measures. Together, these results show how environmental symmetry breaking can organize protein mechanics across scales, linking collective dynamics to the functional sensitivity of individual residues and connecting a general physical mechanism to experimentally measurable protein function.

Sequence heterogeneity is a defining feature of cellular biomolecular condensates, yet how competing interaction motifs encode their thermodynamic stability, internal organization, and dynamics remains poorly understood. Here, we systematically tune the hydrophobicity mismatch between intrinsically disordered peptide pairs to establish sequence hydrophobicity as a programmable determinant of heterotypic condensate behaviour. We show that heterotypic condensates are thermodynamically more stable than homotypic ones having same average hydrophobicity through the cooperative interplay of short-range hydrophobic and long-range electrostatic interactions. Increasing hydrophobicity mismatch drives a composition-dependent transition from homogeneous condensates to core-shell architectures accompanied by pronounced spatial and dynamical heterogeneity, whereas reducing sequence disparity restores homogeneous organization and nearly uniform dynamics. Our results establish a direct molecular link between sequence chemistry, phase stability, condensate architecture, and transport dynamics, providing predictive design principles for engineering synthetic biomolecular condensates with programmable organization and material properties. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/743201v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@12e7fborg.highwire.dtl.DTLVardef@13c31a0org.highwire.dtl.DTLVardef@de3453org.highwire.dtl.DTLVardef@3d4600_HPS_FORMAT_FIGEXP M_FIG C_FIG